1. Field of the Invention
This invention relates to the field of privacy protection and, more particularly to dynamic, data-driven privacy protection relating to telematics data.
2. Description of the Related Art
Vehicles, in effect, have become computing platforms to which mobile services and/or applications can be delivered. Automotive telematics refers to the information-intensive applications presently available and currently under development for use in vehicles. Telematics applications exploit information technology and telecommunications technology to bring useful and time saving services to the domain of vehicles.
Common examples of telematics services can include, but are not limited to, navigation information, emergency roadside assistance, location-based services, delivery of digital information such as electronic mail, entertainment, diagnostics and prognostics, and pay-for-use rental insurance. These applications are made possible through the collection and use of data relating to the location of a vehicle as a function of time, emergency situations including accidents and personal health emergencies, diagnostic data relating to the many systems within a vehicle, services and entertainment selected by the vehicle occupants, the demographics of the driver and passengers, and the behavior of the vehicle driver.
As telematics services become more pervasive, the protection of private user information has taken on an increased significance in light of the fact that existing privacy protection mechanisms are ill suited for dealing with privacy issues in the context of telematics. This is due, in large part, to the dynamic nature of the data needed to provide telematics applications. In essence, the particular services provided to a vehicle and the nature of those services can change as the information received from a vehicle changes. That is, telematics data from vehicles is routinely collected and updated as the information is dynamic and changes over time.
Within conventional computing environments, privacy policies have been developed to protect the confidentiality of private user information. Such policies attempt to protect private user information while still ensuring data sharing to enable useful applications or services. In conventional systems, data is only released if the privacy constraints of the user can be met. Thus, an end-user can be confident that any entity collecting their personal data will not use the data in a manner that is not proscribed by the end-user. Unfortunately, the efficacy of such privacy policy matching systems is completely dependent on the integrity of the people and organizations that provide the services, or otherwise have access to the data.
While some privacy systems have been developed to automatically enforce privacy policies, conventional systems have failed to address the dynamic nature of telematics data and the unique problem set that accompanies the management and protection of telematics data. In other words, the dynamic nature of telematics data—changing in space, time, and with events—means that conventional privacy policy systems based upon static information such as names, addresses, social security numbers, incomes, and the like have limited utility with regard to telematics systems.